docstr: Test `SequentialEncoder.encode_inference()` output
docstr_tok: ["Test","`","SequentialEncoder.encode_inference","(",")","`","output"]
code: def test_encoder_sequence_inference(self):
      """Test `SequentialEncoder.encode_inference()` output"""
      # ==> test prediction <==
      encoder_args = {
          "cyclic": {"past": ["month"], "future": ["month"]}
      }
      encoders = self.helper_encoder_from_model(
          add_encoder_dict=encoder_args
      )
  
      # tests with n <= output_chunk_length
      # with supplying past and future covariates as input
      self.helper_sequence_encode_inference(
          encoders=encoders,
          n=self.n_short,
          past_covariates=self.covariates_multi,
          future_covariates=self.covariates_multi,
          expected_past_idx_ts=self.covariates_multi,
          expected_future_idx_ts=self.covariates_multi,
      )
      # without supplying covariates as input
      self.helper_sequence_encode_inference(
          encoders=encoders,
          n=self.n_short,
          past_covariates=None,
          future_covariates=None,
          expected_past_idx_ts=self.inf_ts_short_past,
          expected_future_idx_ts=self.inf_ts_short_future,
      )
      # tests with n > output_chunk_length
      # with supplying past covariates as input
      self.helper_sequence_encode_inference(
          encoders=encoders,
          n=self.n_long,
          past_covariates=self.covariates_multi,
          future_covariates=None,
          expected_past_idx_ts=self.covariates_multi,
          expected_future_idx_ts=self.inf_ts_long_future,
      )
      # with supplying future covariates as input
      self.helper_sequence_encode_inference(
          encoders=encoders,
          n=self.n_long,
          past_covariates=None,
          future_covariates=self.covariates_multi,
          expected_past_idx_ts=self.inf_ts_long_past,
          expected_future_idx_ts=self.covariates_multi,
      )
  
imports: import copy
  from typing import Optional, Sequence
  import numpy
  import pandas
  import pytest
  from darts import TimeSeries
  from darts.dataprocessing.encoders import FutureCallableIndexEncoder, FutureCyclicEncoder, FutureDatetimeAttributeEncoder, FutureIntegerIndexEncoder, PastCallableIndexEncoder, PastCyclicEncoder, PastDatetimeAttributeEncoder, PastIntegerIndexEncoder, SequentialEncoder
  from darts.dataprocessing.encoders.encoder_base import PastCovariatesIndexGenerator, SingleEncoder
  from darts.dataprocessing.encoders.encoders import CallableIndexEncoder, CyclicTemporalEncoder, DatetimeAttributeEncoder, IntegerIndexEncoder
  from darts.dataprocessing.transformers import Scaler
  from darts.logging import get_logger, raise_log
  from darts.utils import timeseries_generation
label_desc: Use image node_id 3 for calling the TestEncoder obj's underlying member method code with example usage: obj.test_encoder_sequence_inference() without return types